Portraits of Automated Facial Recognition: On Machinic Ways of Seeing the Face This thesis is a timely analysis on the use of automated facial recognition in society, approached through the field of art history and visual studies. The discussion deals with understanding automated facial recognition and its designed algorithms as contemporary modes of seeing and how these produce a new understanding on issues of representation and identity. The first part of this study traces the history of the merging of statistics and vision, examining the example of an early facial recognition algorithm called “eigenface,” while the second part addresses contemporary artistic engagements with facial recognition technology in the work of Thomas Ruff, Zach Blas and Trevor Paglen. This book argues that we must take a closer look at automated facial recognition and claims that this technology is embedded with historical practices of visuality. Even more significantly, this technology, the book argues, is redefining what it means to see and be seen in the contemporary world.